NVIDIA Soars

Reporting in Forbes, Aaron Tilley notes the 300% growth in NVIDIA’s data center business, driven by strong sales of Pascal and Tesla GPU-accelerated chips. According to CEO Jen-Hsun Huang, NVIDIA’s deep learning platform “runs every AI framework, is available in cloud services from Amazon, IBM, Microsoft and Alibaba and in servers from every OEM.” In Fortune, Aaron Pressman explains the role of machine learning in NVIDIA’s growth. He quotes Huang trash-talking Intel’s attempts to accelerate machine learning with FPGA chips.

Software

— In a webinar, Intel delivers an overview of its software accelerators for deep learning, including the Math Kernel Library, the Data Analytics Acceleration Library, and the Deep Learning SDK. Slides here.

Hardware

— Toshiba announces the development of a Time Domain Neural Network that uses an extremely low power consumption neuromorphic semiconductor circuit for deep learning. The technology has the potential to bring deep learning to edge devices, such as sensors and smartphones.

— Nimbix uses NVIDIA Pascal GPUs in its HPC cloud service, while Microsoft Azure uses GPUs based on the old Kepler and Pascal architectures.

Applications

— Researchers at the Fraunhofer Institute for Medical Image Computing in Germany use deep learning to detect tumors in CT and MRI scans.

— In MIT Technology Review, Tom Simonite describes an application that learns the molecular structure of drugs and suggests new structures.

— Researchers from the Swiss Federal Institute in Zurich use ML to measure gender bias in astronomy. First, they build a model to predict citations based on characteristics of a paper (without considering the gender of the lead author.) Then, they used their model to determine the expected number of citations for a set of papers with female lead authors.

— James Anderson summarizes a study that machine learning may be able to diagnose autism from genetic data.

— On the Google Research blog, Malay Haldar et. al. explain how they built a deep neural network to better understand searches on Google Play.

— James Vincent asks: can deep learning help solve lip reading? Researchers at Oxford University’s AI lab publish a paper that documents LipNet, software that does just that.